Die-to-Database Pattern Monitor

High resolution images provide increasingly valuable insight into the nature of yield killing events, so why are fabs wasting them?

Review SEMs are getting faster to meet the increase in demand for high-resolution images. Tens or hundreds of thousands of Review SEM images can be captured in a large fab every day.

But their potential is wasted…

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A picture paints a thousand words, but the rich content of images is reduced to a single class code.

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SEM Non-Visual images discarded. It is not unusual for 50% or more of the SEM images to be SNV.

Every 10 days…

1,440,000 (1.4 million) images are captured.
Valuable SEM and fab cycle time is taken.
Over 700,000 images are thrown away due to SNV.
The other 700,000 images are reduced to single class codes.
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Is there a better way?

Is there a way to extract and retain more information from SEM images?
Is there a way to utilize SNV images as well, for a zero-waste policy?
Is there a way to use these images to continuously monitor patterning quality and process drift in production?

Introducing…
Die-to-Database Pattern Monitor (D2DB-PM)

Every image is analyzed in detail and compared to its reference design.
All critical and consequential features are identified, measured, and tracked.
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Any significant deviation from the intended pattern is identified and highlighted automatically.
SEM Non-Visual (SNV) images are fully utilized. Nothing is thrown away.

Patterning quality and process drift are continuously monitored.

How it works…

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Every image is thoroughly analyzed and decomposed into multiple sub-patterns.

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Sub-patterns and measurements taken on all instances of the patterns are stored and tracked in a relational database.

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Automatic excursion reports are produced, and comprehensive GUI-based analysis use cases are provided.

Some ways of visualizing results…

Summary Table, Pattern Strength and Weakness Box Plot, Contour Gallery, Trend of Selected Patterns.

D2DB Result Visualization

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